Bioaccessibility of As, Cd, Cu, Ni, Pb, and Sb in Toys and Low-Cost Jewelry
Bibliographic record
Abstract
Children can be exposed to toxic elements in toys and jewelry following ingestion. As, Cd, Cu, Ni, Pb, and Sb bioavailability was assessed (n = 24) via the in vitro gastrointestinal protocol (IVG), the physiologically based extraction test (PBET), and the European Toy Safety Standard protocol (EN 71-3), and health risks were characterized. Cd, Cu, Ni, and Pb were mobilized from 19 metallic toys and jewelry (MJ) and one crayon set. Bioaccessible Cd, Ni, or Pb exceeded EU migratable concentration limits in four to six MJ, depending on the protocol. Using two-phase (gastric + intestinal) IVG or PBET might be preferable over EN 71-3 since they better represent gastrointestinal physiology. Bioaccessible and total metal concentrations were different and not always correlated, indicating that bioaccessibility measurement may provide more accurate risk characterization. More information on impacts of multiple factors affecting metals mobilization from toys and jewelry is needed before recommending specific tests. Hazard index (HI) for Cd, Ni, or Pb were >1 for all six MJ exceeding the EU limits. For infants (6-12 mo old), 10 MJ had HI > 1 for Cd, Cu, Ni, or Pb (up to 75 for Cd and 43 for Pb). Research on prolonged exposure to MJ and comprehensive risk characterization for toys and jewelry exposure is recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".